In text categorization, a well-known problem related to document length is that larger term counts in longer documents cause classification algorithms to become biased. The effect of document length can be eliminated by normalizing term counts, thus...
Supervised topic modeling has been successfully applied in the fields of document classification and tag recommendation in recent years. However, most existing models neglect the fact that topic terms have the ability to distinguish topics. In this p...
This paper proposes a short-term frequency-response scheme of a doubly-fed induction generator (DFIG)-based wind turbine generator (WTG) for improving rotor speed recovery and frequency nadir. In the energy-releasing period, to improve the frequency...
This paper proposes a short-term forecasting method for high-frequency broadcast Maximum Usable Frequency (MUF) based on Long Short-Term Memory (LSTM) to meet the demand for refined and precise high-frequency broadcast coverage. Based on the existing...
Short-term wind speed forecasting plays a critical role in enabling the reliable integration of renewable energy and supporting the sustainable operation of power systems. However, traditional dual-frequency decomposition methods oversimplify wind sp...
26 October 2016
Random effect panel data hurdle models are established to research the daily crash frequency on a mountainous section of highway I-70 in Colorado. Road Weather Information System (RWIS) real-time traffic and weather and road surface conditions are me...
This study proposes a hybrid deep learning model based on the Stationary Wavelet Transform (SWT), a Frequency Attention mechanism, and a Temporal Convolutional Network architecture (TCN) for short-term electricity consumption forecasting at the unive...
Real-world power load series exhibit pronounced non-stationarity and complex spatiotemporal dependencies, while the black-box nature of deep learning limits its credibility in industrial dispatching. This paper proposes a probabilistic short-term loa...
Recently, neural network technology has shown remarkable progress in speech recognition, including word classification, emotion recognition, and identity recognition. This paper introduces three novel speaker recognition methods to improve accuracy....
A passive optical resonator is a special sensor used for measurement of lengths on the nanometer and sub-nanometer scale. A stabilized optical frequency comb can provide an ultimate reference for measuring the wavelength of a tunable laser locked to...
Load disaggregation for the identification of specific load types in the total demands (e.g., demand-manageable loads, such as heating or cooling loads) is becoming increasingly important for the operation of existing and future power supply systems....
The rapid expansion of renewable energy has raised the demand for accurate, long-term wind power forecasting. However, wind power series are strongly affected by meteorological factors and exhibit pronounced volatility, making long-term prediction ch...
The swelling of a polymer membrane NafionTM in deionized water and isotonic NaCl and Ringer’s solutions was studied by photoluminescent spectroscopy. According to our previous studies, the surface of this membrane could be considered as a model for a...
To improve the accuracy of predictions and simplify the difficulty with the algorithm, a simplified empirical model is proposed in developing a long-term predictive approach in determining the ionosphere’s F2-layer critical frequency (foF2). Th...
High-frequency water quality monitoring generates large volumes of sub-daily observations, but concise and scalable indicators for diagnosing short-term instability remain limited. Using four-hourly records from 336 national automatic monitoring stat...
Ice loads continue to pose challenges to the structural safety of offshore wind turbines (OWTs), while the rapid development of offshore wind power in cold regions is enabling the deployment of OWTs in deeper waters. To accurately simulate the dynami...
In radar array signal processing, weak nonstationary polarization signal direction of arrival (DOA) estimation is a challenging and significant issue when both strong and weak nonstationary signals coexist. Time-frequency (T-F) analysis is an effecti...
Transcranial alternating current stimulation (tACS) is a neuromodulation procedure that is currently studied for the purpose of improving cognitive function in various diseases. A few studies have shown positive effects of tACS in Alzheimer’s disease...
Sub-synchronous oscillations (SSOs) induced by the interaction between doubly fed induction generators (DFIGs) and weak grids pose a critical threat to the grid-connected stability of DFIG-based wind power systems. In this paper, a dual-damping-term...
In modern electronic warfare, radar intelligence has become increasingly crucial when dealing with complex interference environments. This paper combines radar agile frequency technology with reinforcement learning to achieve adaptive frequency hoppi...
Smartphone-sensors-based human activity recognition is attracting increasing interest due to the popularization of smartphones. It is a difficult long-range temporal recognition problem, especially with large intraclass distances such as carrying sma...
Risk in a power system’s ability to survive imminent disturbances without recourse to low operational cost and non-interruptive energy delivery remains the responsibility of every grid operator. Intermittencies in renewable energy and dynamic l...
High-performance oscillators, atomic clocks for instance, are important in modern industries, finance and scientific research. In this paper, the authors study the estimation and prediction of long-term stability based on convex optimization techniqu...
Offshore wind turbine structures (OWTs) commonly use monopile foundations for support, and long-term exposure to wind–wave cyclic loads may induce changes in foundation stiffness. Variations in foundation stiffness can significantly alter the i...
This paper proposes a new frequency decomposition-based hybrid reactive power forecasting algorithm, EEMD-LSTM-RFR (ELR), which adopts a strategy of frequency decomposition prediction after ensemble empirical mode decomposition and then data reconstr...
The rapid development of wireless communication technology is leading to increasingly scarce spectrum resources, making efficient utilization a critical challenge. This paper proposes a Convolutional Neural Network–Long Short-Term Memory-Integr...
Reliable forecasting of satellite telemetry is critical for spacecraft health management and mission planning. However, conventional data-driven methods often struggle to effectively capture both the long-term dependencies and local dynamics inherent...
Remote sensing of tidal flats and their dynamic changes is essential for understanding and conserving intertidal ecosystems. As a highly dynamic land cover type influenced by tidal variations, tidal flats present challenges for consistent long-term m...
In an ultrasonic system, a piezoelectric transducer (PT) is a key component and contains a piezo element inside. In order to design and operate a system that uses a piezo element for its intended purpose, resonance analysis of the piezo element and a...
The long-term variability and trends in the F2 layer critical frequency variations over Alma-Ata [43.25 N, 77.92 E] for the period 07.1957–04.2018 are studied using near-midday, near-midnight, and hourly median foF2 values. It is shown that the...
There are many time series forecasting methods, but there are few research methods for long-term multivariate time series forecasting, which are mainly dominated by a series of forecasting models developed on the basis of a transformer. The aim of th...
Background/Objectives: Hearing loss is a prevalent sensory impairment in older adults, linked to reduced quality of life, cognitive decline, and social isolation. While it usually begins in the high-frequency range, some individuals present with isol...
Long-term multivariate time series forecasting is crucial for real-world applications, including energy consumption, traffic flow, healthcare, and finance. Usually, some statistical approaches are used for predicting future observations based on hist...
Human alpha oscillation (7–13 Hz) has been extensively studied over the years for its connection with cognition. The individual alpha frequency (IAF), defined as the frequency that provides the highest power in the alpha band, shows a positive...
7 October 2019
Extremely low frequency (ELF) magnetic field (MF) exposure in electric vehicles (EVs) has raised public concern for human health. There have been many studies evaluating magnetic field values in these vehicles. However, there has been no report on th...
In this study, an omnidirectional and high-performance free-standing monopole patch radio-frequency antenna was fabricated using a urea-functionalized phosphorene/TiO2/polypyrrole (UTP) nanocomposite. The UTP nanocomposite antenna was fabricated via...
The time-varying biases within carrier phase observations are integrated into satellite clock offset parameters for precise clock estimation. Consequently, when the precise satellite clock bias is applied to the third frequency observation for precis...
This paper addresses the challenges in extracting content words within the domains of natural language processing (NLP) and artificial intelligence (AI), using sustainable development goals (SDGs) corpora as verification examples. Traditional corpus-...
Low-frequency noise investigation is a highly sensitive and very informative method for characterization of white nitride-based light-emitting diodes (LEDs) as well as for the evaluation of their degradation. We present a review of quality and reliab...
The field of artificial intelligence (AI) is permeating education worldwide, reflecting societal changes driven by advancements in computing technology and the data revolution. Herein, we analyze the alignment between core AI educational curricula an...
Air pollution (mainly PM2.5) is one of the main environmental problems about air quality. Air pollution prediction and early warning is a prerequisite for air pollution prevention and control. However, it is not easy to accurately predict the long-te...
Middle Eastern countries suffer from dust events due to extended arid areas. Among them, Iran is a country experiencing a high record of dust events each year causing major environmental challenges. Although there are previous studies of the present...
This study was aimed at exploring different indices to quantify flow fluctuations and calculate long-term flow indicators (L-FFI). Three approaches were considered to calculate the indicators: Method (1)—calculate the annual index and then aver...
In the Global Navigation Satellite System (GNSS) community, the Quasi-Zenith Satellite System (QZSS) is an augmentation system for users in the Asia-Pacific region. However, the characteristics and performance of four QZSS satellite clocks in a long-...
Historical measurements are usually used to build assimilation models in sequential data assimilation (S-DA) systems. However, they are always disturbed by local noises. Simultaneously, the accuracy of assimilation model construction and assimilation...
Satellite clock bias exhibits complex, time-varying periodic characteristics due to environmental disturbances. Accurate modeling and prediction of periodic terms play a crucial role in improving the precision and stability of short-term predictions....
Given the increase in stroke-related social costs, studies on survival and functional prognosis after stroke are urgently needed. Therefore, we investigated the relationship between the frequency of rehabilitation treatments in the acute and subacute...
Electroencephalogram (EEG) signals are known to contain signatures of stimuli that induce brain activities. However, detecting these signatures to classify captured EEG waveforms is one of the most challenging tasks of EEG analysis. This paper propos...
Background/Objectives: Cochlear implantation (CI) in children with substantial residual hearing remains challenging because of the risk of hearing loss. Partial deafness treatment and hearing preservation have traditionally focused on functionally us...
Converter-interfaced doubly-fed induction generators (DFIGs) can provide short-term frequency support (STFS) capability by releasing rotating kinetic energy. After arresting the frequency decrease, the rotor speed should return to its initial operati...
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